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pro vyhledávání: '"Triclustering"'
Akademický článek
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Autor:
Siswantining, Titin1 (AUTHOR) titin@sci.ui.ac.id, Istianingrum, Maria Armelia Sekar1 (AUTHOR), Soemartojo, Saskya Mary1 (AUTHOR), Sarwinda, Devvi1 (AUTHOR), Saputra, Noval1 (AUTHOR), Pramana, Setia2 (AUTHOR) setia.pramana@stis.ac.id, Prahmana, Rully Charitas Indra3 (AUTHOR) rully.indra@mpmat.uad.ac.id
Publikováno v:
Mathematics (2227-7390). Oct2023, Vol. 11 Issue 19, p4219. 15p.
Autor:
Soares, Diogo F.1 (AUTHOR) dfsoares@ciencias.ulisboa.pt, Henriques, Rui2 (AUTHOR), Gromicho, Marta3 (AUTHOR), de Carvalho, Mamede3 (AUTHOR), Madeira, Sara C.1 (AUTHOR)
Publikováno v:
Scientific Reports. 4/15/2023, Vol. 13 Issue 1, p1-19. 19p.
Autor:
Swathypriyadharsini, P.1 (AUTHOR) swa.pspd@gmail.com, Premalatha, K.1 (AUTHOR) kpl_barath@yahoo.co.in
Publikováno v:
IETE Journal of Research. May2023, Vol. 69 Issue 5, p2328-2336. 9p.
Autor:
Titin Siswantining, Maria Armelia Sekar Istianingrum, Saskya Mary Soemartojo, Devvi Sarwinda, Noval Saputra, Setia Pramana, Rully Charitas Indra Prahmana
Publikováno v:
Mathematics, Vol 11, Iss 19, p 4219 (2023)
Triclustering is a data mining method for grouping data based on similar characteristics. The main purpose of a triclustering analysis is to obtain an optimal tricluster, which has a minimum mean square residue (MSR) and a maximum tricluster volume.
Externí odkaz:
https://doaj.org/article/cff1e69e08ad4cb7a96ce20aa462bb01
Publikováno v:
LNCS (2020)
In this paper, we describe versions of triclustering algorithms adapted for efficient calculations in distributed environments with MapReduce model or parallelisation mechanism provided by modern programming languages. OAC-family of triclustering alg
Externí odkaz:
http://arxiv.org/abs/2010.12933
Autor:
HENRIQUES, RUI1 rmch@tecnico.lisboa.pt, MADEIRA, SARA C.2 sacmadeira@ciencias.ulisboa.pt
Publikováno v:
ACM Computing Surveys. Sep2019, Vol. 51 Issue 5, p1-43. 43p. 2 Diagrams, 5 Charts, 2 Graphs.
Publikováno v:
In Journal of Biomedical Informatics October 2022 134
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-19 (2023)
Abstract This work proposes a new class of explainable prognostic models for longitudinal data classification using triclusters. A new temporally constrained triclustering algorithm, termed TCtriCluster, is proposed to comprehensively find informativ
Externí odkaz:
https://doaj.org/article/aeda5f20019943c8bdd18a1af2ac3892